Sequential, Multiplexed Immunofluorescent Imaging of Live Cells Based on DNA-Mediated Reversible Fluorophore Attachment/Detachment with Antibodies
Given the spectral overlap of fluorophores, traditional immunofluorescence imaging is limited by the number of proteins that can be imaged simultaneously. Although sequential imaging techniques have been proposed, in which repeated staining and destaining are performed to obtain the merged image of several proteins, they are applied only to fixed cells presumably due to their harsh conditions. Therefore, observation and analysis of live cells have not been achieved with the sequential imaging approach. In this study, we develop a sequential, multiplexed immunofluorescence imaging method for live cells using DNA as a detachable linker to bind antibodies to fluorophores. The use of toehold-mediated strand displacement of DNAs enables the attachment and detachment of fluorophores under mild physiological conditions. Consequently, at least six imaging cycles and the simultaneous use of three different fluorophores are demonstrated in live A431 and A549 cells, indicating the potential of imaging numerous protein markers in a single sample. Furthermore, by performing sequential staining at different time points, the dynamic expression changes of multiple proteins (EGFR, CD44, and Integrin β1) during EGF stimulation can also be detected. This approach is expected to facilitate comprehensive analysis of complex protein networks and their spatiotemporal regulation in live cells.
Authors
- Seiichi Ohta (ORCID: https://orcid.org/0000-0002-4775-8199)
- Li Xu (ORCID: https://orcid.org/0000-0003-3309-2944)
- Noriko Nakamura (ORCID: https://orcid.org/0000-0002-0037-8973)
- Yuki Maeda
Institutions
- Japan Science and Technology Agency (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- JACS Au
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1021/jacsau.5c00752
- Citations
- 1
- Primary Topic
- Advanced biosensing and bioanalysis techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.81